Skip to content
Agentmart
Submit a tool

business-behavior-testing

Select and write risk-based behavior tests for features or bug fixes.

Skill by terebentina

IndexedMIT
Write a review

Chalk Labs

Need help deploying business-behavior-testing?

Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.

Book a call

Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/terebentina-business-behavior-testing

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

Get the weekly diff

The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.

We use your email only for this newsletter. Privacy

About

Select and write risk-based behavior tests for features or bug fixes. Use when deciding what to test, where to test it, or whether an agent-written test is worth keeping.

Use cases: testing, writing, agent-building

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/business-behavior-testing

What's inside

Skill name
business-behavior-testing
Description
Select and write risk-based behavior tests for features or bug fixes. Use when deciding what to test, where to test it, or whether an agent-written test is worth keeping.
License
MIT
Instructions
19 lines in SKILL.md · view on GitHub

Files (2)

  • SKILL.md
  • openai.yaml · agents/

SKILL.md (first lines)

# Business behavior testing

Protect consequential behavior, not implementation steps. BDD-style scenarios may help name a rule; Gherkin and a red-green cycle are not requirements.

## Select scenarios

1. Read the ticket/spec, relevant domain vocabulary, and existing tests. State the user or business outcome being changed and a plausible regression that would matter (including money, access, data loss, or an important workflow). Check whether existing tests already catch it.
2. Keep a scenario only if it distinguishes correct behavior from that regression through an observable result. Cover the normal outcome and materially different rules or transitions when their failure matters. No test quota: one scenario can suffice; a risky rule can need several; if existing coverage suffices, add none.
3. Choose the narrowest **public seam** that exercises the real rule and its necessary collaborators: a domain/service API, command, or request boundary. Use the real business logic; control only external I/O, clock, or nondeterminism. Go end-to-end when the risk is in the wiring across boundaries, not by default.
4. Assert independently known outcomes from the spec or a worked example. For example, a discount-precedence test asserts the final payable amount for an eligible cart, not that `applyDiscount` was called. Name tests for the rule and outcome, not the method or branch.
5. If a bug has a suitable seam, observe the regression test fail before fixing it, then pass afterward. For a feature, write a test when it protects a selected scenario; implementation can precede a test when discovery makes the rule clearer. In every case, exercise the changed path and run the relevant existing tests.

## Keep or delete

A test earns its place when a plausible harmful change makes it fail while a behavior-preserving refactor leaves it green. Prefer existing coverage over duplicates. Remove tests that assert mocks echo inputs, private calls, copies, incidental defaults, wording, or code structure; use a throwaway smoke check instead when a permanent test would add no protection. Do not weaken coverage of consequential security, financial, or data-integrity rules to meet a test count.

Report the chosen seam, protected rule(s), and verification evidence. If no new test is warranted, say what existing coverage or smoke check protects the change.

From terebentina/skills, MIT.

More from terebentina/skills

Signals

Stars
0
Forks
1
Open issues
0
Last commit (this folder)
Sep 24, 2026 (1 month ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from terebentina

Done for you

Rather not set it up yourself?

Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.

See how we build AI agents →Read the case studies

Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.

launches shipped
50+
launches shipped
media placements
500+
media placements
founders on every account
2
founders on every account

Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block

Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.

Get business-behavior-testing running in your business

Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.

Goes to the Chalk Labs founders, not the newsletter. Privacy

Need help deploying business-behavior-testing?

CallGet help
Cite this page

business-behavior-testing skill. Agent Mart. https://agentmart.dev/skills/terebentina-business-behavior-testing (last updated 2026-10-24)